基于全信息初值优化的GM(1,1)模型在物流行业中的应用

The Application of GM(1,1)Model Based on Initial Value Optimization of Total Information in Logistics Industry

针对传统灰色GM(1,1)模型预测精度不高的缺点,提出了基于全信息初值优化的GM(1,1)模型,并探讨其参数求解方法。首先,根据“新信息优先”“信息充分利用”等原理构造了全信息初值,对原始序列每一个分量进行加权构造全信息初值,然后构建非线性规划求解初值参数,最后利用构建的模型预测我国物流行业发展规模,并对比传统灰色模型预测结果,发现新模型具有更高的模拟预测精度。

Aiming at the shortcoming of the traditional grey GM(1,1)model with low prediction accuracy,a GM(1,1)model based on total information initial value optimization was proposed,and its parameter solving method was discussed.Firstly,the initial value of total information is constructed according to the principles of“new information priority”and“full use of information”.Each component of the original sequence is weighted to construct the initial value of total information,and then nonlinear programming is constructed to solve the initial value parameters.Finally,the established model is used to predict the development scale of China's logistics industry.Compared with the prediction results of the traditional grey model,it is found that the new model has higher simulation prediction accuracy.